Abstract
AbstractBackgroundTeamwork has become a central element of engineering education. However, the race‐ and gender‐based marginalization prevalent in society is also prevalent in engineering student teams. These problematic dynamics limit learning opportunities, isolate historically marginalized students, and ultimately push students away from engineering, further reinforcing the demographic imbalances in the profession.PurposeWhile there are strategies to improve the experiences of marginalized students within teams, there are few tools for detecting marginalizing behaviors as they occur. The purpose of this work is to examine how peer evaluations collected as a normal part of an engineering course can be used as a window into team dynamics to reveal marginalization as it occurs.MethodWe used a semester of peer evaluation data from a large engineering course in which a team project is the central assignment and peer evaluation occurs four times during the course. We designed an algorithm to identify teams where marginalization may be occurring. We then performed qualitative analyses using a sociolinguistic analysis.ResultsResults show that the algorithm helps identify teams where marginalization occurs. Qualitative analyses of four illustrative cases demonstrated the stealth appearance and evolution of marginalization, providing strong evidence that hidden within language of peer evaluation are indicators of marginalization. Based on the wider dataset, we present a taxonomy (eight categories) of linguistic marginalization appearing in peer comments.ConclusionBoth peer evaluation scores and the language used in peer evaluations can reveal team inequities and may serve as a near‐real‐time mechanism to interrupt marginalization within engineering teams.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.